EP3808692A1 - Verfahren zur vorhersage von fehlern in einem fahrgastbewegungssystem - Google Patents

Verfahren zur vorhersage von fehlern in einem fahrgastbewegungssystem Download PDF

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Publication number
EP3808692A1
EP3808692A1 EP19382901.7A EP19382901A EP3808692A1 EP 3808692 A1 EP3808692 A1 EP 3808692A1 EP 19382901 A EP19382901 A EP 19382901A EP 3808692 A1 EP3808692 A1 EP 3808692A1
Authority
EP
European Patent Office
Prior art keywords
moving system
passenger moving
passenger
stopping distance
data
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
EP19382901.7A
Other languages
English (en)
French (fr)
Inventor
Francisco Canteli Alvarez
Ignacio Muslera Fernández
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
TK Elevator Innovation Center SA
Original Assignee
ThyssenKrupp Elevator Innovation Center SA
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by ThyssenKrupp Elevator Innovation Center SA filed Critical ThyssenKrupp Elevator Innovation Center SA
Priority to EP19382901.7A priority Critical patent/EP3808692A1/de
Priority to EP20789991.5A priority patent/EP4045449A1/de
Priority to PCT/EP2020/078930 priority patent/WO2021074236A1/en
Priority to BR112022007160A priority patent/BR112022007160A2/pt
Priority to CN202080072449.2A priority patent/CN114585582A/zh
Priority to US17/754,760 priority patent/US20240017966A1/en
Publication of EP3808692A1 publication Critical patent/EP3808692A1/de
Withdrawn legal-status Critical Current

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Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B66—HOISTING; LIFTING; HAULING
    • B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
    • B66B25/00—Control of escalators or moving walkways
    • B66B25/006—Monitoring for maintenance or repair
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B66—HOISTING; LIFTING; HAULING
    • B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
    • B66B29/00—Safety devices of escalators or moving walkways
    • B66B29/005—Applications of security monitors
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B66—HOISTING; LIFTING; HAULING
    • B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
    • B66B5/00—Applications of checking, fault-correcting, or safety devices in elevators
    • B66B5/0006—Monitoring devices or performance analysers
    • B66B5/0018—Devices monitoring the operating condition of the elevator system
    • B66B5/0025—Devices monitoring the operating condition of the elevator system for maintenance or repair

Definitions

  • the invention refers to a method of predicting deterioration in a brake system comprised within a passenger moving system and use of said method in a passenger moving system.
  • Passenger moving systems including escalators, moving walks and elevators are stopped at various times for various reasons during their lifetime.
  • a "stop" signal Once a "stop" signal has been registered, the moving panels of an escalator or moving walk or the cabin of the elevator, experience first a reduction in speed before coming to a halt. During this stopping process, vibrations and friction between the moving components occur.
  • a "stop" command can be affected within a short space of time and the corresponding stopping distance covers the shortest distance. This distance is normally measured in millimeters (mm). Over time however, due to everyday "wear and tear" on the moving system, this stopping distance gradually increases and continues to increase until it reaches a point where safety is compromised. All moving systems comprise a control unit that is configured to shut down a moving system in the event this stopping distance becomes too large and no longer complies with safety requirements, for example, the code or regulation EN115, B44.
  • Some passenger moving systems comprise display units that communicate to the technician the nature of the fault. Some systems comprise no such display unit, leaving the technician to perform a full check-up of the passenger moving system in order to deduce where the fault lies. Regardless of whether there is a display or not, this process is time consuming for the technician, expensive for the customer and causes significance inconvenience to passengers because the passenger moving system has to rendered "out of order".
  • EP 3363758 A1 discloses a mechanism for monitoring the operation of a passenger transport device.
  • US patent 5785165 discloses a data collection and analysis system for passenger conveyors.
  • neither of these documents address the problem of faults in the braking system directly, nor do they address the problem of being able to predict a fault in the braking system before it occurs.
  • no two passenger moving systems are the same, which means a prediction for a first system would not necessarily be the same for a second system.
  • the invention refers to a method of predicting deterioration in a brake system comprised within a passenger moving system.
  • Passenger moving systems preferably include escalators, elevators, and moving walks.
  • the method preferably comprises the method steps of;
  • the one or multiple sensor(s) is/are preferably in communication with the control unit via a wireless connection or via hardware.
  • the control unit is preferably in communication with a cloud via a wireless connection or hardware.
  • the method steps c. to d. are repeated over a specified time period.
  • the specified time period preferably refers to a number of hours, a number of days, a number of weeks or a number of months.
  • the period of time covers at least a month having up to 31 days so that a comparison of data "from month-to-month" is possible.
  • a command signal initiating a maintenance operation is triggered
  • a maintenance operation preferably includes
  • This method can be carried out over a specified time period, preferably constantly over a specified time period.
  • the method can be adapted to acquire data at pre-defined time intervals over this time period. For example, the method can be performed:
  • a filter operation is applied after step (e) to determine any trend in the stopping distance. This advantageously ensures that only useful data is taken into consideration and any "abnormal" data is prevented from skewing results and negatively affecting the excessive stopping distance.
  • the pre-determined threshold is set according to a code of regulation pertaining to the specific type of passenger moving system.
  • This advantageously provides for a "tailor-made" method that can be applied to any type of passenger moving system.
  • Table 1 and table 2 provide details from the code of regulation EN115 relating to excessive stopping distances for escalators and moving walks respectively.
  • Table 1 - stopping distances for escalators Nominal speed v Stopping distance between 0,5 m/s 0.20 m and 1.00 m 0.65 m/s 0.30 m and 1.30 m 0.75 m/s 0.4.
  • the specified time period is one selected from the group comprising:
  • the pre-defined time intervals for acquiring data within the specified time period can be any one selected from the group comprising:
  • the invention relates to a use of the method as outlined above in a passenger moving system.
  • the passenger moving system is selected from the group comprising:
  • Fig. 1 shows a schematic diagram of a passenger moving system 10 implementing a method 100 according to an embodiment of the invention.
  • the moving walkway 10 is an escalator wherein the escalator comprises a control unit 100 and at least one movable panel 101.
  • the control unit 100 is in communication with a gateway device (not shown), for example, a computer or portable laptop wherein e.g., the computer is equipped with the required software to communicate with the control unit 100 allowing for the condition of the escalator 10 to be constantly monitored. Only one sensor is required to carry out this method, however in this example, three are shown.
  • a first sensor 11 is positioned such that it measures the movement of at least one movable panel 101 about the exit of the escalator 10.
  • a second sensor 12 is positioned such that it measures the movement of at least one movable panel 101 about the middle of the escalator 10 and a third sensor n is positioned such that it measures the movement of at least one movable panel 101 about the entrance of the escalator 10.
  • the sensors 11, 12, n used in this particular example are magnetic sensors. It is also possible to position the one or more sensor in the motor (not shown) or in the main shaft (not shown) so that said sensor(s) can sense any starting and stopping.
  • the sensors 11, 12, n are activated each time the relevant moving panel 101 passes by the sensor 11, 12, n during the looped transit. When the moving panels begin to stop, data acquisition begins and the stopping distance is continuously measured until the panels come to a complete stop. An analysis of the stopping operation, in particular the excessive stopping distance is performed at the control unit 100 thereby providing a forecast on the condition of the brake system (not shown). This analysis involves the method outlined in steps 101 to 110.
  • Steps 101 to 103 are performed at the control unit 100 of the passenger moving system.
  • Step 101 requires the gathering of data relating to the stopping distance each time the moving walkway 10 is stopped.
  • Step 101 is initiated upon activation of at least one sensor 11, 12, n.
  • Step 102 involves calculating the corresponding stopping distance.
  • This information is then transmitted to an interface module in step 103.
  • the interface module is an internet of things (IoT) device, e.g., a cloud.
  • the calculated distance(s) is/are pre-processed in step 104, this involves basic filtering of data.
  • the pre-processed data is then sent to a database in step 105.
  • the database can be comprised of hardware e.g., a USB, or be located in a cloud.
  • the control unit 100 is adapted to send this information to the database in order to perform data analysis and processing.
  • step 106 processing is carried out in step 106 allowing the data to be filtered in step 107.
  • Filtering involves removing outliers in order to take into account the behavior, normal or otherwise of the escalator 10. This includes for example, removing any stopping data which was recorded when the unit was travelling at a speed different to the nominal speed, or when the stopping data was recorded when the escalator 10 was stopped "abnormally", e.g.,
  • the stopping distance will be abnormal and thus not a true reflection of a braking operation under normal conditions. If the escalator is stopped for travelling in the wrong direction, the stopping distance will be small due to the slow speed achieved by the escalator in that short space of time. If the escalator is moving at a higher speed and the emergency brake is triggered, the stopping distance will be larger. Should any of these situations arise, the escalator will stop in the normal way, however the corresponding data readings are described as "abnormal" and are thus preferably discounted during processing. A variation of several mm or less, e.g., (2 to 20 mm) in the stopping distance over a time period of e.g. one week is considered as "normal". During the monitoring of the stopping distance over a specified time period, e.g., 31 days, a constant increase in stopping distance is expected due to increased wear on the brake. The data is then analyzed in step 108.
  • Analysis 108 can include
  • step 109 a result is obtained in step 109.
  • an alert will be generated in step 110 to inform the relevant party, e.g., the customer; a building services manager; a technician, that the brake of the escalator 10 needs to be inspected and where necessary, repaired, replaced or adjusted.
  • Fig. 2 shows a flow diagram of the method steps as outlined in figure 1 .
  • Figure 3 shows the difference in the recorded data before and after analysis between steps 101 and 108.
  • the top graph corresponds to step 101 wherein data points are recorded for each day.
  • the x-axis represents the time each time the escalator stops. There can be several points recorded per day.
  • the y-axis details the stopping distance in millimeters, which runs from 240 mm to 280 mm.
  • the middle graph shows the recorded data after having been filtered in step 107.
  • the data points in the first graph which have an arrow depict "abnormal" readings and are discounted in the filtering step thus reducing the number of total data points.
  • the middle graph has an x-axis detailing the dates, and a y-axis detailing the stopping distance in millimeters, which runs from 255 mm to 280 mm.
  • the bottom graph shows the recorded data after a final analysis is carried out in step 108 and provides a result (step 109).
  • An average data point is recorded to represent the reading over a particular week.
  • the x-axis details the "number of weeks", in this particular example, the time period is 6 weeks.
  • the y-axis details the stopping distance in millimeters, which now runs from 268 mm to 276 mm. If, in this particular example the pre-determined threshold for the stopping distance was 280 mm, no alert would be triggered since the maximum stopping distance recorded was 276 mm. Thus the escalator 10 would be allowed to continue to operate as normal.
  • the pre-determined threshold value was 275 mm or 276 mm
  • the highest recorded value of 276 mm reaches or surpasses this threshold, thus an alert signal is generated to initiate a maintenance operation i.e., inform the relevant party, e.g., the customer; a building services manager; a technician, that the brake of the escalator 10 needs to be inspected and where necessary, repaired, replaced or adjusted.
  • the alert signal can be triggered at any step within the method as shown in fig. 2 .
  • the control unit 100 sends the measurements of the stopping distance based on the sensor 11, 12, n inputs to the cloud.

Landscapes

  • Escalators And Moving Walkways (AREA)
  • Valves And Accessory Devices For Braking Systems (AREA)
EP19382901.7A 2019-10-15 2019-10-15 Verfahren zur vorhersage von fehlern in einem fahrgastbewegungssystem Withdrawn EP3808692A1 (de)

Priority Applications (6)

Application Number Priority Date Filing Date Title
EP19382901.7A EP3808692A1 (de) 2019-10-15 2019-10-15 Verfahren zur vorhersage von fehlern in einem fahrgastbewegungssystem
EP20789991.5A EP4045449A1 (de) 2019-10-15 2020-10-14 Verfahren zur vorhersage von fehlern in einem fahrgastbewegungssystem
PCT/EP2020/078930 WO2021074236A1 (en) 2019-10-15 2020-10-14 A method to predict faults in a passenger moving system
BR112022007160A BR112022007160A2 (pt) 2019-10-15 2020-10-14 Um método para prever falhas em um sistema de movimento de passageiro
CN202080072449.2A CN114585582A (zh) 2019-10-15 2020-10-14 用于预测乘客移运***中故障的方法
US17/754,760 US20240017966A1 (en) 2019-10-15 2020-10-14 A method to predict faults in a passenger moving system

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
EP19382901.7A EP3808692A1 (de) 2019-10-15 2019-10-15 Verfahren zur vorhersage von fehlern in einem fahrgastbewegungssystem

Publications (1)

Publication Number Publication Date
EP3808692A1 true EP3808692A1 (de) 2021-04-21

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Family Applications (2)

Application Number Title Priority Date Filing Date
EP19382901.7A Withdrawn EP3808692A1 (de) 2019-10-15 2019-10-15 Verfahren zur vorhersage von fehlern in einem fahrgastbewegungssystem
EP20789991.5A Pending EP4045449A1 (de) 2019-10-15 2020-10-14 Verfahren zur vorhersage von fehlern in einem fahrgastbewegungssystem

Family Applications After (1)

Application Number Title Priority Date Filing Date
EP20789991.5A Pending EP4045449A1 (de) 2019-10-15 2020-10-14 Verfahren zur vorhersage von fehlern in einem fahrgastbewegungssystem

Country Status (5)

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US (1) US20240017966A1 (de)
EP (2) EP3808692A1 (de)
CN (1) CN114585582A (de)
BR (1) BR112022007160A2 (de)
WO (1) WO2021074236A1 (de)

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5785165A (en) 1996-10-30 1998-07-28 Otis Elevator Company Data collection and analysis system for passenger conveyors
US20180029839A1 (en) * 2016-07-29 2018-02-01 Otis Elevator Company Speed detection system of passenger conveyor and speed detection method thereof
US20180032598A1 (en) * 2016-07-29 2018-02-01 Otis Elevator Company Big data analyzing and processing system and method for passenger conveyor
EP3363758A1 (de) 2017-02-15 2018-08-22 KONE Corporation Mechanismus zur überwachung des betriebs einer personenbeförderungsvorrichtung

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5785165A (en) 1996-10-30 1998-07-28 Otis Elevator Company Data collection and analysis system for passenger conveyors
US20180029839A1 (en) * 2016-07-29 2018-02-01 Otis Elevator Company Speed detection system of passenger conveyor and speed detection method thereof
US20180032598A1 (en) * 2016-07-29 2018-02-01 Otis Elevator Company Big data analyzing and processing system and method for passenger conveyor
EP3363758A1 (de) 2017-02-15 2018-08-22 KONE Corporation Mechanismus zur überwachung des betriebs einer personenbeförderungsvorrichtung

Also Published As

Publication number Publication date
BR112022007160A2 (pt) 2022-06-28
US20240017966A1 (en) 2024-01-18
WO2021074236A1 (en) 2021-04-22
EP4045449A1 (de) 2022-08-24
CN114585582A (zh) 2022-06-03

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